• Journal of the Korea Safety Management & Science
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• v.3 no.3
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• pp.65-75
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• 2001

This research fundamentally deals with an analysis of service level for a multi-level inventory distribution system which is consisted of a central distribution center and several branches being supplied stocks from the distribution center, Under continuous review policy, the distribution center places an order for planned order quantity to an outside supplier, and the order quantity is received after a certain lead time. Also, each branch places an order for particular quantity to its distribution center, and receives the order quantity after a lead time. In most practical distribution environment, demands and lead times are generally not fixed or constant, but variable. And these variabilities make the analysis more complicated. Thus, the main objective of this research is to suggest a method to compute the service level at each depot, that is, the distribution center and each branch with variable demands and variable lead times. Further, the model will give an idea to keep the proper level of safety stocks that can attain effective or expected service level for each depot.

• Journal of Korean Society for Quality Management
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• v.47 no.1
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• pp.87-96
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• 2019

Purpose: The purpose of this paper is to determine an optimal production time for economic production quantity model with preventive maintenance and random defective rate as the function of a machinery deteriorates. Methods: If a machinery shifts from "in-control" state to "out-of-control" state, a proportion of defective items being produced increases. It is assumed that time to state shift is a random variable and follows an arbitrary distribution. The elapsed time until process shift decreases stochastically as a production cycle repeats and quasi-renewal process is used to implement for production facilities to deteriorate. Results: When the exponential parameter for exponential distribution increases, the optimal production time increases. When Weibull distribution is considered, the optimal production time is closely affected by the shape parameter of Weibull distribution. Conclusion: A mathematical model is suggested to find optimal production time and optimal number of production cycles and numerical examples are implemented to validate the patterns for changes of optimal times under different parameters assumptions. The real application is implemented using the proposed approach.

• Journal of the Korean Statistical Society
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• v.19 no.2
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• pp.139-144
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• 1990

For the first-order bilinear time series model $X_t = aX_{t-1} + e_i + be_{t-1}X_{t-1}$ where ${e_i}$ is a sequence of independent normal random variables with mean 0 and variance $\sigma^2$, the asymptotic distribution of sample autocarrelation function is obtained and shown to follow a normal distribution. The variance of the asymptotic distribution is of a complicated form and hence a bootstrap estimate of the variance is proposed for large sample inference. This result can be used to distinguish between different bilinear models.

• Journal of Korean Institute of Industrial Engineers
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• v.31 no.2
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• pp.120-126
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• 2005

Until now, the traditional production models and logistics have developed a broader strategic approach called supply chain. However, there are some obstacles to apply industry practice because of unrealistic assumptions. The most serious of them is that they assume the lead times are integer multiples of the planning time grid. This assumption makes it difficult to express the processing and transportation lags correctly. Thus, in this paper, we propose a new methodology for the integrated production/distribution model having non-integer time lags using the concept of dynamic production function. In case that the time lags are integer or non-integer, the dynamic production function reflects well the situation under given environments. Experiments show that the proposed model can express the real system more accurately than the prior model can.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.2D
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• pp.233-239
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• 2006

Most research for until at now link travel time were research for mean link travel time calculate or estimate which uses the average of the individual vehicle. however, the link travel time distribution is divided caused by with the impact factor which is various traffic condition, signal operation condition and the road conditional etc. preceding study result for link travel time distribution characteristic showed that the patterns of going through traffic were divided up to 2 in the link travel times. therefore, it will be more accurate to divide up the link travel time into the one involving delay and the other without delay, rather than using the average link travel time in terms of assessing the traffic situation. this study is it analyzed transit hour distribution characteristic and a cause using examine to the variables which give an effect at link travel time distribute using simulation program and determinate link travel time distribute ratio estimation model. to assess the distribution of the link travel times, this research develops the regression model and the fuzzy model. the variables that have high level of correlations in both estimation models are the rest time of green ball and the delay vehicles. these variables were used to construct the methods in the estimation models. The comparison of the two estimation models-fuzzy and regression model- showed that fuzzy model out-competed the regression model in terms of reliability and applicability.

• Journal of the Korean Data and Information Science Society
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• v.25 no.4
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• pp.921-929
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• 2014

A bivariate exponential distribution with a location parameter is proposed as a model for a two-component shared load system with a guarantee time. Some statistical properties of the proposed model are investigated. The maximum likelihood estimators and uniformly minimum variance unbiased estimators of the parameters, mean time to failure, and the reliability function of system are obtained with unknown guarantee time. Simulation studies are given to illustrate the results.

• Journal of Information Technology Applications and Management
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• v.24 no.2
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• pp.71-80
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• 2017

Software reliability is one of the most elementary and important problems in software development In order to find the software failure occurrence, the instantaneous failure rate function in the Poisson process can have a constant, incremental or decreasing tendency independently of the failure time. In this study, we compared the reliability performance of the software reliability model using the parameters of Pareto life distribution with the intensity decreasing pattern and the shape parameter of Erlang life distribution with the intensity increasing and decreasing pattern in the software product testing. In order to identify the software failure environment, the parametric estimation was applied to the maximum likelihood estimation method. Therefore, in this paper, we compare and evaluate software reliability by applying software failure time data. The reliability of the Erlang and Pareto life models is shown to be higher than that of the Pareto lifetime distribution model when the shape parameter is higher and the Erlang model is more reliable when the shape parameter is higher. Through this study, the software design department will be able to help the software design by applying various life distribution and shape parameters, and providing basic knowledge using software failure analysis.

• Proceedings of the Korea Society for Simulation Conference
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• 1999.04a
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• pp.6-10
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• 1999

We present a simulation result to the analysis of the effects of cell residence time distributions upon the expected channel occupancy time based on an analytic mobility model. Numerical examples show that exponential distribution provides upper and lower bound to the expected channel occupancy times of new calls and handoff calls. This fact reveals that the assumption of exponential distribution as the cell residence time distribution as the cell residence time distribution may over- or under-estimate cellular mobile systems.

• Journal of Internet of Things and Convergence
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• v.9 no.3
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• pp.1-6
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• 2023

One of the economical ways to satisfy the quality of service desired by the user in a web service environment is to adjust the size of the object. To this end, this study finds the maximum size of objects that satisfy this constraint when the mean response time is given below an arbitrary threshold for quality of service. It can be inferred that in the steady state of system, the mean response time in the deterministic model by using the round-robin will be the same as that of the queueing model following the general distribution. Based on this, analytical formulas and procedures for finding the maximum object size are obtained. As a service distribution of web traffic, the Pareto distribution is appropriate, so the maximum object size is computed by applying the M/G(Pareto)/1 model and the M/G/1/PS model using exponential distribution as computational experience. Performance evaluation through numerical calculation shows that as the shape parameter in the Pareto distribution increases, the M/G(Pareto)/1 model and M/G/1/PS model have the same maximum object size. The results of this study can be used to environments where objects can be sized for economical web service control.

• Journal of the Korea Institute of Military Science and Technology
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• v.16 no.5
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• pp.639-645
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• 2013

The aim of the study is to investigate the method to estimate a storage life of propelling charge on the decrease of muzzle velocity by stochastic gamma process model. It is required to establish criterion for state failure to estimate the storage life and it is defined in this paper as a muzzle velocity difference between reference value and maximum allowable standard deviation multiplied by 6. The relationship between storage time and muzzle velocity is investigated by nonlinear regression analysis. The stochastic gamma process model is used to estimated the state distribution and the life distribution for storage time for 155mm propelling charge KM4A2 because the regression analysis is a deterministic method and it can't describe the distribution of life for storage time.